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基于数值和人工智能的研究,研究了制GFRP RHS配置文件的设计准则的开发,这些配置文件受到网络伤的影响
Raheel Asghar1,2, Muhammad Faisal Javed3, Mujahid Ali4
1College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao, 266590, China.
Scientific reports
|May 2, 2024
概括
这项研究使用数值和人工智能方法研究了在玻璃纤维增强聚合物 (GFRP) 矩形空心截面 (RHS) 中的网. 新的设计准则准确地预测了这些GFRP RHS配置文件的网络伤能力.
科学领域:
- 结构工程 结构工程
- 材料科学 材料科学 材料科学
- 计算力学 计算力学 计算力学
背景情况:
- 玻璃纤维增强聚合物 (GFRP) 越来越多地用于结构应用.
- 网页残疾是空洞部分配置文件的关键故障模式.
- 现有的GFRP配置文件设计准则可能无法完全捕捉复杂的行为.
研究的目的:
- 通过数值和基于人工智能的研究,对压GFRP矩形空隙截面 (RHS) 配置文件的网性能进行调查.
- 开发和验证一个有限元模型来预测网络.
- 制定基于人工智能的设计指南,用于GFRP RHS配置文件的网络.
主要方法:
- 在ABAQUS CAE.中开发和验证有限元模型.
- 为了建立一个全面的数据库,进行了广泛的参数研究.
- 基于人工智能 (AI) 的基因表达编程 (GEP) 的应用,用于设计准则的制定.
主要成果:
- 网能力与断面厚度和轴承长度直接相关.
- 网页残疾能力与截面宽度,高度,角径和轮长度相反相关.
- 基于人工智能的修改设计规则准确地预测了网络的容量.
结论:
- 开发的数值和基于人工智能的方法为网络伤能力提供了准确的预测.
- 制定的设计指南为GFRP RHS配置文件的安全设计做出了重大贡献.
- 需要进一步的研究来完善和完成最终应用的设计准则.
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